Deriving Differential Target Propagation from Iterating Approximate Inverses

29 July 2020

Papers citing "Deriving Differential Target Propagation from Iterating Approximate Inverses"

17 / 17 papers shown

Title
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation Satoki Ishikawa Rio Yokota Ryo Karakida 49 0 0 04 Nov 2024
Gradient-Free Training of Recurrent Neural Networks using Random Perturbations Jesus Garcia Fernandez Sander Keemink Marcel van Gerven AAML 50 4 0 14 May 2024
A Review of Neuroscience-Inspired Machine Learning Alexander Ororbia A. Mali Adam Kohan Beren Millidge Tommaso Salvatori 40 7 0 16 Feb 2024
Fixed-Weight Difference Target Propagation Tatsukichi Shibuya Nakamasa Inoue Rei Kawakami Ikuro Sato AAML 24 3 0 19 Dec 2022
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations Axel Laborieux Friedemann Zenke 41 33 0 01 Sep 2022
A Theoretical Framework for Inference and Learning in Predictive Coding Networks Beren Millidge Yuhang Song Tommaso Salvatori Thomas Lukasiewicz Rafal Bogacz 34 12 0 21 Jul 2022
A Theoretical Framework for Inference Learning Nick Alonso Beren Millidge J. Krichmar Emre Neftci 22 16 0 01 Jun 2022
Minimizing Control for Credit Assignment with Strong Feedback Alexander Meulemans Matilde Tristany Farinha Maria R. Cervera João Sacramento Benjamin Grewe 22 17 0 14 Apr 2022
Gradients without Backpropagation A. G. Baydin Barak A. Pearlmutter Don Syme Frank Wood Philip Torr 38 66 0 17 Feb 2022
Towards Scaling Difference Target Propagation by Learning Backprop Targets M. Ernoult Fabrice Normandin A. Moudgil Sean Spinney Eugene Belilovsky Irina Rish Blake A. Richards Yoshua Bengio 19 28 0 31 Jan 2022
Target Propagation via Regularized Inversion Vincent Roulet Zaïd Harchaoui BDL AAML 27 4 0 02 Dec 2021
Benchmarking the Accuracy and Robustness of Feedback Alignment Algorithms Albert Jiménez Sanfiz Mohamed Akrout OOD AAML 25 8 0 30 Aug 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 28 7 0 30 Jun 2021
Credit Assignment in Neural Networks through Deep Feedback Control Alexander Meulemans Matilde Tristany Farinha Javier García Ordónez Pau Vilimelis Aceituno João Sacramento Benjamin Grewe 31 35 0 15 Jun 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods Shiyu Duan José C. Príncipe MQ 38 3 0 09 Jan 2021
Self Normalizing Flows Thomas Anderson Keller Jorn W. T. Peters P. Jaini Emiel Hoogeboom Patrick Forré Max Welling 30 14 0 14 Nov 2020
Biological credit assignment through dynamic inversion of feedforward networks William F. Podlaski C. Machens 27 19 0 10 Jul 2020